PhishingAgent: an agentic workflow method for advanced phishing email detection by JIN Jiandong, HUANG Zheng, HU Zhanyu, ZOU Yuanxin, QIN Huidong, LAI Qingnan, YANG Jia, ZHOU Changling

“…PhishingAgent integrated multi-source knowledge bases and security tools to fully leverage the reasoning capabilities of large language model (LLM), enhancing the precision and depth of identifying complex phishing email attacks. The agentic workflow was built on a dual-system reasoning framework, a rapid detection system facilitates efficient preliminary threat identification, followed by a deep reasoning system that conducted detailed semantic analysis and contextual inference, significantly improving the interpretability of results. …”
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A Method of Fatigue Driving State Detection Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei

“…Most of those algorithms have complex structure, low efficiency and weak adaptability in face of driver’s individual behavior habit. …”
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Tower view object detection based on ECIOU structure embedded in YOLO by QIAN Jide, YAN Hao, LIANG Yan, ZENG Changchang, MOU Yihao

“…In view of the problems that the existing tower view target detection system is prone to large positioning deviation and low small target detection accuracy，this paper proposes an aircraft target detection method based on the ECIOU structure embedded in the YOLO v8 model from the tower view to improve the accuracy and efficiency of detection. …”
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Lightweight Infrared Small Target Detection Method Based on Linear Transformer by Bingshu Wang, Yifan Wang, Qianchen Mao, Jingzhuo Cao, Han Zhang, Laixian Zhang

“…However, their applications in infrared small target detection is limited due to two factors: (1) the high computational complexity of the conventional transformer models reduces the efficiency of detection; (2) the small target is easily left out in the visual environment with complex backgrounds. …”
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Structural Fault Detection and Diagnosis for Combine Harvesters: A Critical Review by Haiyang Wang, Liyun Lao, Honglei Zhang, Zhong Tang, Pengfei Qian, Qi He

“…Combine harvesters, as essential equipment in agricultural engineering, frequently experience structural faults due to their complex structure and harsh working conditions, which severely affect their reliability and operational efficiency, leading to significant downtime and reduced agricultural productivity during critical harvesting periods. …”
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A lightweight MHDI-DETR model for detecting grape leaf diseases by Zilong Fu, Lifeng Yin, Can Cui, Yi Wang

“…This structure is designed to overcome the challenges of capturing complex high-level and subtle low-level features, and it uses Efficient Local Attention to focus more efficiently on regions of interest, thereby enhancing the model’s ability to detect complex targets while improving accuracy and inference speed. …”
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A Tunnel Surface Diseases Detection Algorithm Based on YOLOv4 by LI Jia, QIU Xinhua, JI Yuwen

“…Aiming at the problem that tunnel environment is complex and variable and the contrast of surface image is low, which makes the traditional pattern recognition method cannot effectively detect diseases. …”
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Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

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Pavement Disease Visual Detection by Structure Perception and Feature Attention Network by Bin Lv, Shuo Zhang, Haixia Gong, Hongbo Zhang, Bin Dong, Jianzhu Wang, Cong Du, Jianqing Wu

“…Balancing detection performance and computational efficiency is critical for sustainable pavement disease detection in energy-constrained scenarios. …”
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YOLO-DAFS: A Composite-Enhanced Underwater Object Detection Algorithm by Shengfu Luo, Chao Dong, Guixin Dong, Rongmin Chen, Bing Zheng, Ming Xiang, Peng Zhang, Zhanwei Li

“…Additionally, a SCSA module is inserted before the detection head to fully utilize multi-semantic information, improving the detection performance in complex underwater scenes. …”
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Leveraging U-Net and ASPP for effective fault detection in photovoltaic modules by Khalfalla Awedat, Masoud Alajmi, Mustafa Elfituri

“…Abstract The efficiency of photovoltaic (PV) systems is often compromised by undetected faults, exacerbated by the complexity of thermal imagery backgrounds. …”
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Curb Detection and Mapping via Robust Iterative Gaussian Process Regression by Di Wang, Si Chen, Zhenni Ma, Jiajia Shi, Fuchun Zhang

“…Curb detection and mapping are of great importance to ensure the safety and efficiency of intelligent vehicles. …”
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Obstacle detection and avoidance system based on layered costmaps for robot tractors by Ricardo Ospina, Kota Itakura

“…This paper presents a novel obstacle detection and avoidance system based on layered costmaps, designed to enhance the safety and efficiency of robot tractors navigating farm roads. …”
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Improvement of RT-DETR model for ground glass pulmonary nodule detection. by Siyuan Tang, Qiangqiang Bao, Qingyu Ji, Tong Wang, Naiyu Wang, Min Yang, Yu Gu, Jinliang Zhao, Yuhan Qu, Siriguleng Wang

“…This article proposed an algorithm based on RT-DETR model with the following enhancement: 1) optimize the backbone network with FCGE blocks to increase the detection accuracy of small-sized and blurred edge nodules; 2) replace the AIFI module with HiLo-AIFI module to reduce redundant computation and improve the detection accuracy of pure ground glass pulmonary nodules and mixed ground glass pulmonary nodules; 3) replace the DGAK module with CCFF module to address the issue of capturing complex features and recognition of irregularly shaped ground glass nodules. …”
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AS-TBR: An Intrusion Detection Model for Smart Grid Advanced Metering Infrastructure by Hao Ma, Yifan Fan, Yiying Zhang

“…In terms of global dependency modeling, existing models struggle to dynamically adjust key features, impacting the efficiency and accuracy of intrusion detection and response. …”
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Advancing Rice Disease Detection in Farmland with an Enhanced YOLOv11 Algorithm by Hongxin Teng, Yudi Wang, Wentao Li, Tao Chen, Qinghua Liu

“…The C3k2-CSCBAM block in the neck region reduces the training overhead and boosts target learning in complex backgrounds. Additionally, a lightweight 320 × 320 LSDECD detection head improves small-object detection. …”
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Underground personnel detection and tracking using improved YOLOv7 and DeepSORT by Weiqiang FAN, Xuejin WANG, Yinghui ZHANG, Xiaoyu LI

“…Based on this, an improved YOLOv7 and DeepSORT underground personnel detection and tracking algorithm is proposed. First, in order to be able to extract more critical underground personnel image features and improve the model's adaptability in the complex scene of coal mine underground, the SimAM attention mechanism is incorporated into the Neck module of YOLOv7, and the improved YOLOv7 model is used to detect underground personnel targets. …”
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Application of VUV/Sulfite Defluorination System for the Simple Detection of Perfluoroalkyl Substances by Shiyong Tao, Yilin Chen, Xiao Mei, Luyao Jin, Feng Wu, Jing Xu

“…Overall, this work presents a simple and cost-effective indirect analytical strategy of applying a VUV/sulfite defluorination system for individual PFAS quantitative detection in complex environmental matrices.…”
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Artificial intelligence-driven predictive framework for early detection of still birth by Sarah A. Alzakari, Asma Aldrees, Muhammad Umer, Lucia Cascone, Nisreen Innab, Imran Ashraf

“…Predictive modeling is becoming increasingly popular in the context of early disease detection. The use of machine learning approaches for predictive modeling can help early detection of diseases thereby enabling medical experts to appropriate medical treatments. …”
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An Improved 2D Pose Estimation Algorithm for Extracting Phenotypic Parameters of Tomato Plants in Complex Backgrounds by Yawen Cheng, Ni Ren, Anqi Hu, Lingli Zhou, Chao Qi, Shuo Zhang, Qian Wu

“…We enhanced a novel heatmap-free method, YOLOv8s-pose, by integrating the Convolutional Block Attention Module (CBAM) and Content-Aware ReAssembly of FEatures (CARAFE), to develop an improved YOLOv8s-pose (IYOLOv8s-pose) model, which efficiently focuses on salient image features with minimal parameter overhead while achieving a superior recognition performance in complex backgrounds. …”
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